On the Detection of High-Quality, High-Density Electromyograms During 80m Sprints: a Case Study

Surface electromyograms (EMGs) have been often used to study muscle function in locomotor activities. Typically, EMGs are sampled with a single pair of electrodes, providing information on the timing and degree of muscle excitation. Additional information may be obtained when sampling EMGs with multiple electrodes from the same, target muscles. Studies using high-density EMGs (HD-EMGs) in locomotor activities are limited to laboratory settings and low speed tasks, likely due to the technical shortcomings in the commercially available systems for high-density recordings. This issue is further aggravated when kinematics data are necessary for associating EMGs with events of interest during the movement cycle. By combining two systems, ad hoc developed for the on-field recording of kinematics data and HD-EMGs, here we present single-case results during extreme-speed locomotion-the 80 m sprint on an official, athletic track. Our aim was to verify whether descriptors of quality documented in the EMG literature during well-controlled, isometric contractions, apply to the HD-EMGs we detected and segmented with respect to the running cycles. From a single, elite sprinter, we were able to obtain HD-EMGs with negligible movement artifacts and with temporal profiles typically characterizing action potentials of single motor units. Our results would seem to advocate the possibility of using HD-EMG to study muscle function during highly dynamic contractions outside the laboratory settings

Running speed changes the distribution of excitation within the biceps femoris muscle in 80m sprints

Predictors and mitigators of strain injuries have been studied in sprint-related sports. While the rate of axial strain, and thus running speed, may determine the site of muscle failure, muscle excitation seemingly offers protection against failure. It seems therefore plausible to ask whether running at different speeds changes the distribution of excitation within muscles. Technical limitations undermine however the possibility of addressing this issue in high-speed, ecological conditions. Here we circumvent these limitations with a miniaturized, wireless, multi-channel amplifier, suited for collecting spatio-temporal data and high-density surface electromyograms (EMGs) during overground running. We segmented running cycles while 8 experienced sprinters ran at speeds close to (70% and 85%) and at (100%) their maximum, over an 80 m running track. Then we assessed the effect of running speed on the distribution of excitation within biceps femoris (BF) and gastrocnemius medialis (GM). Statistical parametric mapping (SPM) revealed a significant effect of running speed on the amplitude of EMGs for both muscles, during late swing and early stance. Paired SPM revealed greater EMG amplitude when comparing 100% with 70% running speed for BF and GM. Regional differences in excitation were observed only for BF however. As running speed increased from 70% to 100% of the maximum, a greater degree of excitation was observed at more proximal BF regions (from 2% to 10% of the thigh length) during late swing. We discuss how these results, in the context of the literature, support the protective role of pre-excitation against muscle failure, suggesting the site of BF muscle failure may depend on running speed

Base of Support, Step Length and Stride Width Estimation during Walking Using an Inertial and Infrared Wearable System

The analysis of the stability of human gait may be effectively performed when estimates of the base of support are available. The base of support area is defined by the relative position of the feet when they are in contact with the ground and it is closely related to additional parameters such as step length and stride width. These parameters may be determined in the laboratory using either a stereophotogrammetric system or an instrumented mat. Unfortunately, their estimation in the real world is still an unaccomplished goal. This study aims at proposing a novel, compact wearable system, including a magneto-inertial measurement unit and two time-of-flight proximity sensors, suitable for the estimation of the base of support parameters. The wearable system was tested and validated on thirteen healthy adults walking at three self-selected speeds (slow, comfortable, and fast). Results were compared with the concurrent stereophotogrammetric data, used as the gold standard. The root mean square errors for the step length, stride width and base of support area varied from slow to high speed between 10–46 mm, 14–18 mm, and 39–52 cm2, respectively. The mean overlap of the base of support area as obtained with the wearable system and with the stereophotogrammetric system ranged between 70% and 89%. Thus, this study suggested that the proposed wearable solution is a valid tool for the estimation of the base of support parameters out of the laboratory

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice